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This article is part of the supplement: The ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (IJCBS)

Open Access Research

Recent advances in clustering methods for protein interaction networks

Jianxin Wang12*, Min Li1*, Youping Deng3 and Yi Pan2

Author affiliations

1 School of Information Science and Engineering, Central South University, Changsha 410083, China

2 Department of Computer Science, Georgia State University, Atlanta, GA30303, USA

3 Rush University Cancer Center, Rush University Medical Center, Chicago, IL 60612, USA

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Citation and License

BMC Genomics 2010, 11(Suppl 3):S10  doi:10.1186/1471-2164-11-S3-S10

Published: 1 December 2010

Abstract

The increasing availability of large-scale protein-protein interaction data has made it possible to understand the basic components and organization of cell machinery from the network level. The arising challenge is how to analyze such complex interacting data to reveal the principles of cellular organization, processes and functions. Many studies have shown that clustering protein interaction network is an effective approach for identifying protein complexes or functional modules, which has become a major research topic in systems biology. In this review, recent advances in clustering methods for protein interaction networks will be presented in detail. The predictions of protein functions and interactions based on modules will be covered. Finally, the performance of different clustering methods will be compared and the directions for future research will be discussed.